Population Health Management commonly leads practitioners to identify a cohort that will have an intervention applied. As a rule of thumb most analysts will work with pseudonymised data sets. For targeted interventions patients require re-identification; this process is generally carried out by a third party organisation. As third party organisations work with many health care providers they have a strict set of requirements. This has been based around SW CSU's required formatting.
cohort_processing(
df,
Split_by,
path,
prefix = "DSCRO",
com_code = "11M",
date_format = "%Y%m%d",
suffix = "_REID_V01"
)a tidy dataframe in standard Master Patient Index format ie SangerTools::PopHealthData.
A column within df that will be used to split the patients and will also appear in the file name. Ideally should be a health organisation code such as GP Practice Code or Hospital Trust Code. Should only have alpha-numeric values
A file path to which the CSV files will be written
File name prefix, default is "DSCRO" See more here: NHS DSCRO
Commissioner Code, default is "11M"; Gloucestershire.
A date format passed internally to `format(Sys.Date())`; will form part of file name to denote date of generation. You can read more about date formatting in R from R lang
A file name suffix, default is "_REID_V01", To be left as blank use "", without spaces.
n number of CSV files written to the location specified by path argument.